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Postgraduate Diploma in Data Analytics ( Postgraduate Diploma )

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Accreditations

Euclea Business School, France College De Paris

The Postgraduate Diploma in Data Analytics provides learners with an in-depth, interdisciplinary understanding of the application of data analytics to solve real-world business and technological problems. 

The programme combines the principles of data science, artificial intelligence, cybersecurity, and innovation management to prepare learners for the dynamic and evolving needs of data-centric industries.

The curriculum integrates professional, analytical, and technical skills with ethical considerations and global perspectives. Learners engage with statistical techniques, machine learning, big data technologies, and decision-making frameworks, underpinned by contemporary academic and industry practices. Practical components ensure graduates are industry-ready, with the competence to handle, analyse, and communicate data effectively

Eucléa Business School is a higher education institution that is a member of the Collège de Paris, specialised in business, technology and alternating management. With four campuses strategically located in Strasbourg, Metz, Mulhouse and Reims, Eucléa offers a complete range of training, ranging from Post-Bac to Bac+5 level. Our school is dedicated to pedagogical excellence and personal development. Euclea’s goal is to help you develop your skills, explore new perspectives and prepare for a bright future while fostering a student life rich in opportunities.

 

Component

No.

Full

Module Code

Module Title

Compulsory / Core / Optional

NQF Level

Credits

PGDA01

COM101

Managing Innovation and Computing

Core

Level 7

10

PGDA01

DAT105

Business Intelligence Systems

Core

Level 7

10

PGDA01

SEC121

Implementing and Managing Cybersecurity

Core

Level 7

10

PGDA01

SDU124

System development and Use Experience(UX)

Core

Level 7

10

PGDA01

AI105

Artificial Intelligence

Core

Level 7

10

PGDA01

BDA109

Big Data Analytics

Core

Level 7

10

PGDA01

ML123

Machine Learning

Core

Level 7

10

PGDA01

DIV101

Data Insights and Visualisation

Core

Level 7

10

PGDA0

BDA110

Business Data Analytics

Core

Level 7

10

  • Eligibility Check
  • Application Submission
  • Application Acceptance
  • Provisional Admission
  • Document Verification
  • Admission acceptance

 

A.  Knowledge and understanding

Learning outcomes

A1

Demonstrate critical understanding of the role of innovation, cybersecurity, and business intelligence in organisational computing.

A2

Evaluate statistical, algorithmic, and visualisation techniques for data-driven insight and evidence-based decision-making.

A3

Apply core and emerging data science and AI techniques, including machine learning and big data, within business contexts.

A4

Appraise and integrate cloud-based and enterprise-level tools for managing, analysing, and visualising structured and unstructured data.

Learning methods

Lectures and Seminars, Workshops and Labs, Case Studies and Simulations, Individual and Group Projects, Industry Guest Lectures, Online Learning and VLE

Assessment methods

Essays, case analyses, timed assessments, research reports

B.  Intellectual/cognitive skills

Learning outcomes

B1

Analytical reasoning in business/data problems

B2

Ethical/legal frameworks in cybersecurity and AI

B3

Critical engagement with innovation and analytics strategy

Learning methods

Lectures and Seminars, Workshops and Labs, Case Studies and Simulations, Individual and Group Projects, Industry Guest Lectures, Online Learning and VLE

Assessment methods

Essays, case analyses, timed assessments, research reports

C.  Practical and professional skills

Learning outcomes

C1

Statistical and visual analysis (Data Analysis & Visualisation)

C2

Machine learning implementation (Machine Learning)

C3

Big data tools like Hadoop/Spark (Big Data Analytics)

C4

Cybersecurity management (Cybersecurity)

Learning methods

Lectures and Seminars, Workshops and Labs, Case Studies and Simulations, Individual and Group Projects, Industry Guest Lectures, Online Learning and VLE

Assessment methods

Essays, case analyses, timed assessments, research reports

D.  Key Skills

Learning outcomes

D1

Communication

Communicate effectively in oral and written forms, including academic reports, presentations, and visual data interpretations, tailored to diverse audiences.

D2

Information Technology

Use a variety of digital tools and platforms including data analytics software, databases, coding environments, and cloud services in solving real-world data problems.

D3

Numeracy

Apply quantitative and statistical methods to analyse data, interpret trends, and generate valid conclusions using appropriate mathematical models.

D4

Problem solving

Identify, investigate, and resolve complex problems using data-driven approaches, algorithmic thinking, and critical analysis.

D5

Working with others

Operate effectively within teams, contributing to group objectives, resolving conflict, and collaborating in diverse professional and intercultural settings.

D6

Improving own learning and performance

Demonstrate autonomy and reflective practice in setting learning goals, monitoring performance, and engaging in continuous professional development.

 

 

Learning methods

Lectures and Seminars, Workshops and Labs, Case Studies and Simulations, Individual and Group Projects, Industry Guest Lectures, Online Learning and VLE

Assessment methods

Essays, case analyses, timed assessments, research reports

  • Euclea Business School, France
  • College De Paris

  • A Bachelor’s degree (2:2 or above) in Computing, Business, Engineering, Mathematics, or a related field.

  • English language proficiency equivalent to IELTS 6.0 or higher.

  • Recognition of Prior Learning (RPL) is available for candidates with a minimum of 5 years of industry experience in relevant domains.

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